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Solution · Customer serviceAfter the treatment the patient is not left alone with a sheet of paper, and every sign of concern reaches the doctor within minutes
Aftercare and the follow-up visit
Right after the visit the patient receives the instructions your doctors wrote for her treatment and a link to a follow-up visit at the time the clinic’s protocol sets. A few days later a robot asks briefly how she feels, and every answer signalling concern goes straight to the doctor in Teams as a call to make. The robot gives no advice and assesses nothing; it makes sure nothing is overlooked.
Executive summary
After a treatment the patient leaves with an aftercare sheet that soon gets lost, books the follow-up if she remembers, and sends her questions on Instagram in the evening or calls in the morning when reception has its hands full.
A robot sends the instructions for that treatment right after the visit, proposes a follow-up at the time set by the clinic’s protocol, and a few days later asks how she feels; every sign of concern goes straight to the doctor in Teams.
More follow-ups kept on time, a faster doctor response when something causes concern, fewer calls about things the instructions already answer; a relationship that ends with a plan for the next treatment rather than silence.
instructions and messages from the doctors’ templates; follow-up visits in the clinic system or Bookings; a duty-doctor channel in Microsoft Teams; SMS and email to patients
Business problem
The treatment ends in the treatment room, but the clinic’s responsibility lasts for weeks
For the patient the treatment does not end when she gets up from the chair. Over the following days she watches the result, follows the instructions and has questions: is this normal, when can I exercise again, should this change have gone by now. Yet all she received is an aftercare sheet handed over at reception, at the moment she was thinking about payment and parking. The sheet disappears into her handbag before she gets home.
The follow-up visit the doctors ask for only gets booked today if reception manages to mention it on the way out. On a Friday afternoon, with a queue at the till, it does not always manage. The patient promises to call, and usually calls only when something worries her. And a follow-up meant to be a calm conversation about the result and the next steps turns into an anxious phone call.
Post-treatment questions arrive through the worst channels. An Instagram message at 11 pm, a call at 8:05 am as reception opens the day’s calendar. Some of them the instructions would settle, if the patient had them at hand; some need a doctor, and quickly. Today both land in the same queue, and chance decides how fast a signal reaches the doctor.
Good aftercare is not more work, just better order: instructions on the patient’s phone, the follow-up in the calendar and a clear route by which concern reaches the doctor. The first two a robot does alone. The third it prepares so that the doctor gets the signal within minutes and can do what no robot can: call and assess.
How it works today
Below is what the work looks like before anything is automated.
- PersonAfter the treatment the patient gets an aftercare sheet at the till
- WaitingA follow-up gets booked only if reception manages to mention it
- Risk of errorQuestions come on Instagram in the evening, on the reception phone in the morning
- WaitingA sign of concern waits in the same queue as questions about parking
- Risk of errorThe patient remembers the follow-up when something worries her
- WaitingThe relationship ends in silence instead of a plan for the next treatment
Why the current process costs more than it appears
The bill that never shows up in a budget.
- How many planned follow-ups took place last quarter, and how many did nobody book?
- How many post-treatment calls and messages concern things that were in the instructions?
- How fast does a message from a worried patient reach a doctor today, especially in the evening?
- How many follow-ups end with a conversation about next steps, and how many never get the chance to happen?
Cost of inaction
The model assumes a clinic with about 600 treatment visits a month, some of which require a follow-up under the protocol. The value of a follow-up lies not in its price, which is often included in the treatment, but in the conversation about the result and the next steps.
The most important line has no amount: the time that passes before a doctor learns that something worries the patient. Here we count minutes, not euros.
A model organisation with realistic proportions – the numbers exist so you can run the same maths on your own data; they are not a client result.
An aesthetic clinic: 3 treatment rooms, 5 doctors and cosmetologists, about 600 treatment visits a month, Microsoft 365, appointments in the clinic system. Instructions on paper, follow-ups booked on the way out.
Friday, 4:30 pm: a patient finishes a filler treatment. At 5 pm she receives a text and an email with the instructions the clinic’s doctors wrote for this treatment and a link to a follow-up visit at the time set by the clinic’s protocol.
The patient picks a follow-up slot on Saturday morning, from her sofa. The visit appears in the schedule of the doctor who performed the treatment.
Monday: the robot sends a short wellbeing question with three answers to choose from. The patient chooses “something worries me” and adds a sentence.
In the same minute the duty doctor sees an alert in Teams with the patient’s name, the treatment type and date, and her sentence; the “call back” task has a deadline set by the clinic. The patient automatically receives only a confirmation that the doctor will contact her, with the clinic’s information for emergencies. The doctor calls a quarter of an hour later, assesses and decides.
At the follow-up two weeks later the doctor discusses the result and the plan for the next treatment. In the modelled quarter two thirds more follow-ups take place than before. These are model figures, not the clinic’s records.
Proposed solution
We start with the doctors: for each treatment type they write down the aftercare instructions, the follow-up timing from the clinic’s protocol and the wording of a short wellbeing question. They also decide what the robot should reply to a patient reporting concern, usually a one-line confirmation and information on what to do in an emergency. None of this content is created on our side.
After each treatment the robot works alone: it sends the instructions by text and email, proposes a follow-up with a link to the right doctor’s free slots, reminds her the day before, and on the agreed day sends the wellbeing question. “All fine” closes the thread, “I have a question” goes to the reception queue, and “something worries me” goes immediately to the duty doctor in Teams, with the treatment details and a call-back task due within the time the clinic sets.
The boundary is absolute: the robot answers no medical questions, assesses no symptoms, offers no reassurance and recommends nothing beyond the content the doctors prepared. Its job is to shorten the path from the patient to the doctor, not to replace it. All communication stays in the visit record, with dates and content, so the doctor sees the history before picking up the phone.
UiPath Orchestrator: the post-treatment dispatch schedule, follow-up reminders, an alert queue and an audit trail of every message; UiPath Integration Service connectors to Outlook 365, SharePoint and Teams
Instructions and questions from the doctors’ templates for each treatment, automatic follow-up proposals, three answer paths, a duty-doctor alert with a call-back task and a communication log in the record
The clinic system or Microsoft Bookings with doctors’ schedules via export or API; an SMS gateway on your own provider contract
How the automated process works
- AutomationRight after the visit the instructions for this treatment arrive by text and email
- AutomationA follow-up link at the protocol’s timing, with the doctor who treated her
- SystemA few days later, a short wellbeing question with three answers
- Automation“Something worries me” goes straight to the duty doctor in Teams
- PersonThe doctor calls, assesses and decides; the robot advises nothing
- PersonAt the follow-up the doctor discusses the result and next steps with the patient
Human-in-the-loop model
Automation handles
- Sending the instructions for the specific treatment and proposing a follow-up with a reminder
- The wellbeing question and routing the answers into three paths
- A duty-doctor alert with a call-back task and a communication log in the record
People decide
- The instructions, the follow-up protocol and the reply to a concern: set by the doctors
- Assessing symptoms, talking to the patient and every medical decision: the doctor alone
- Answering non-medical questions from the queue: reception
Before and after
Systems and integrations
The stack is short on purpose: one engine, one execution layer, one place where a person decides.
Inputs
- completed visits with treatment type from the clinic system
- instructions, follow-up protocols and message templates from the doctors
- doctors’ schedules with free slots
- patients’ answers to the wellbeing question
Automation layer
- UiPath Orchestrator
- UiPath Robots
- UiPath Integration Service
- UiPath Action Center
Target systems
- instructions and follow-up proposals delivered to patients
- alerts with call-back tasks in the duty-doctor channel in Teams
- a communication log in the visit record
Human touchpoints: the doctor calls back after an alert; reception answers non-medical questions; doctors review templates when a protocol changes
Technologies used
the dispatch schedule, reminders, the alert queue, a trail of every message
Aduty-doctor alerts, the reception queue, emails to patients
Afollow-up slots with the right doctor via connector, export or API
Bcompleted visits and the communication log in the record via export or API
Binstructions, reminders and questions; on your own provider contract
BIllustrative economic model
Numbers you can check against your own data.
The model assumes some patients who attend a follow-up plan their next treatment there; a conversation that would not happen at all without the follow-up. The value of a fast doctor response is deliberately not counted in euros. Put your own figures into the calculator beside.
Run the maths on your data
An illustrative estimate based on your inputs. It models freed capacity, not promised savings.
Business benefits
- Every patient has the instructions for her treatment on her phone, not on a lost sheet
- Follow-ups happen on time, not when something worries her
- A sign of concern reaches the doctor within minutes, evenings and weekends too
- Reception takes fewer calls about questions the instructions answer
- The follow-up becomes a conversation about the result and the plan, not an anxious call
The management view
- A clinic that guides the patient after treatment builds trust that returns as further visits and referrals
- A clear path from concern to doctor lowers the risk of overlooking a signal that needed a response
- A complete post-treatment communication log sits in the record, ready for any question
Board-level KPIs
follow-ups kept on time · time from a reported concern to the doctor’s call · post-treatment questions at reception · share of patients answering the wellbeing question · follow-ups ending with a plan for the next treatment
Security and governance
The automation has exactly the permissions it needs. Not one more.
- Messages contain only content prepared by the doctors; the robot creates no advice and assesses no symptoms
- Patients’ answers are health data: they go into the record and are visible only to authorised doctors, in line with GDPR
- A concern alert has a response time set by the clinic and a trail: who took it, when they called back
- Every message sent and every answer is logged: what, when, to whom
- Data stays in your Microsoft 365 tenant; the robots run in the EU region of UiPath Automation Cloud
Why now
Patients expect contact after treatment as after any other premium service; a sheet at the till is no longer enough.
Post-treatment questions come anyway, just through the worst channels; better that they come along a route the clinic controls.
A quick-win deployment takes weeks, and the doctors’ templates serve the clinic for years.
Relevant executive roles
Follow-ups in the schedule, relationships that end with a plan, and order in post-treatment communication
Gets a sign of concern within minutes, with the history, instead of by chance via reception
Has the instructions at hand, the follow-up in her calendar, and knows someone is watching
Common questions and objections
No. The robot sends content prepared by the doctors and routes reports of concern to a doctor. It does not assess, reassure or advise. The only automatic reply to a concern is a confirmation that the doctor will be in touch, in wording set by the clinic.
The clinic decides who is on duty and when, and what the robot replies outside those hours, usually information on what to do in an emergency. The alert waits for the assigned doctor with a trail, so nothing gets lost in an inbox.
Yes. Each treatment type has its own set: instructions, whether and when a follow-up, whether a wellbeing question. The doctors decide once, and the robot applies it at every visit.
When this is not the right solution
- A clinic without written aftercare instructions: the doctors prepare them first, then the robot delivers them
- Expecting the automation to replace the doctor in assessing complications: this solution shortens the path to the doctor, it does not replace them
- No patient consent to contact by SMS or email: then the phone remains and the robot only keeps the list
A question for the next management meeting
How many post-treatment follow-ups did not take place last quarter only because nobody booked them?
Implementation approach
Scope without ambiguity, before anything is signed.
We deliver
- Instructions, follow-up protocols and questions written with the doctors for each treatment
- Automatic dispatch after the visit and a follow-up proposal with a reminder
- Three answer paths and a duty-doctor alert with a call-back task
- A log of all communication in the visit record
- A handbook for doctors and reception and two weeks of assistance after go-live
We need from you
- Two hours with the doctors for instructions, follow-up protocols and the reply to a concern
- Duty rules: who takes alerts and during which hours
- Access to visits and schedules in the clinic system or Bookings
Stages
Discovery
Treatments, today’s instructions, follow-ups and question channels; half a day at the clinic
Protocols
Instructions, follow-up timing, questions and replies written with the doctors
Build
Dispatches, follow-ups, questions, answer routing, alerts, the record log
Parallel run
Two weeks on selected treatments; the doctors review the alerts and content
Go-live
All treatments in the new mode; a follow-up review after the first month
A quick win. Most of the work is a one-off write-up of instructions and protocols with the doctors; after that the aftercare for every treatment runs by itself, and the doctor steps in where needed.
Monday, 10:12 am: a patient writes that something worries her. At 10:12 the doctor has an alert, at 10:27 they are on the phone. No queue, no chance.
Count the follow-ups planned last quarter and those that took place. Send us both numbers with the list of treatments that require a follow-up; we will send back an aftercare design and the arithmetic of what returns to the clinic.
Check how many follow-ups never happenThe neighbouring process usually has the same problem
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See the solutionIndustries where we deploy this most oftenAesthetic medicineSmall business & services